Yong Fan, PhD

faculty photo
Associate Professor of Radiology
Department: Radiology
Graduate Group Affiliations

Contact information
Department of Radiology
Perelman School of Medicine
University of Pennsylvania
Richards Building, 7th floor
3700 Hamilton Walk
Philadelphia, PA 19104-6116
Office: 215-746-4065
PhD (Pattern Recognition and Intelligent Systems)
Chinese Academy of Science, 2003.
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Description of Research Expertise

Dr. Fan has a broad background in medical image analysis and pattern recognition, with specific training in applied mathematics, statistics, and machine learning.

His research interests are in the field of imaging analytics, machine learning, pattern recognition, and more generally in computational imaging. Much of his work has been focusing on methodology development and applications of machine learning techniques that quantify morphology and function from medical images, integrate multimodal information to aid diagnosis and prediction of clinical outcomes, and guide personalized treatments. The methodological focus has been on the general field of artificial intelligence, with emphasis on machine learning methods applied to complex and large imaging and clinical data. The image analytic methods being and to be developed include functional connectomics, radiomics, image registration and segmentation, and personalized neuromodulatory therapies. On the clinical side, his primary focus is on applications in clinical neuroscience, in cancer, and in chronic kidney disease, aiming to develop precision diagnostic tools using machine learning and pattern recognition techniques. The clinical research studies include brain development, brain diseases such as Alzheimer's, schizophrenia, depression, and addiction, pediatric kidney diseases, and predictive modeling of treatment outcomes of cancer patients such as rectal and lung cancers.

Selected Publications

Li Y, Li H, Fan Y: ACEnet: Anatomical Context-Encoding Network for Neuroanatomy Segmentation. Med Image Anal 70(101991): 1-12, May 2021 Notes: https://doi.org/10.1016/j.media.2021.101991.

Jiao Z, Li H, Xiao Y, Aggarwal C, Galperin-Aizenberg M, Pryma D, Simone CB 2nd, Feigenberg SJ, Kao GD, Fan Y: Integration of Risk Survival Measures Estimated From Pre- and Posttreatment Computed Tomography Scans Improves Stratification of Patients With Early-Stage Non-small Cell Lung Cancer Treated With Stereotactic Body Radiation Therapy Int J Radiat Oncol Biol Phys 109(5): 1647-1656, Apr 2021 Notes: https://doi.org/10.1016/j.ijrobp.2020.12.014.

Li H, Fan Y: MDReg-Net: Multi-resolution diffeomorphic image registration using fully convolutional networks with deep self-supervision. Hum Brain Mapp 43(7): 2218-2231, May 2022 Notes: https://doi.org/10.1002/hbm.25782.

Li H, Fan Y: Interpretable, highly accurate brain decoding of subtly distinct brain states from functional MRI using intrinsic functional networks and long short-term memory recurrent neural networks. Neuroimage 202(116059): 1-11, Nov 2019 Notes: https://doi.org/10.1016/j.neuroimage.2019.116059.

Yin S, Peng Q, Li H, Zhang Z, You X, Fischer K, Furth SL, Fan Y, Tasian GE: Multi-instance Deep Learning of Ultrasound Imaging Data for Pattern Classification of Congenital Abnormalities of the Kidney and Urinary Tract in Children. Urology 142: 183-189, Aug 2020 Notes: https://doi.org/10.1016/j.urology.2020.05.019.

Zheng Q, Itkin M, Fan Y: Quantification of Thoracic Lymphatic Flow Patterns Using Dynamic Contrast-enhanced MR Lymphangiography. Radiology 296(1): 202-207, Jul 2020 Notes: https://doi.org/10.1148/radiol.2020192337.

Liu H, Li H, Habes M, Li Y, Boimel P, Janopaul-Naylor J, Xiao Y, Ben-Josef E, Fan Y: Robust Collaborative Clustering of Subjects and Radiomic Features for Cancer Prognosis. IEEE Trans Biomed Eng 67(10): 2735-2744, Oct 2020 Notes: https://doi.org/10.1109/tbme.2020.2969839.

Smith AL, Weissbart SJ, Hartigan SM, Bilello M, Newman DK, Wein AJ, Malykhina AP, Erus G, Fan Y: Association between urinary symptom severity and white matter plaque distribution in women with multiple sclerosis. Neurourol Urodyn 39(1): 339-346, Jan 2020 Notes: https://doi.org/10.1002/nau.24206.

Yin S, Peng Q, Li H, Zhang Z, You X, Fischer K, Furth SL, Tasian GE, Fan Y: Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks. Med Image Anal 60(101602): 1-14, Feb 2020 Notes: https://doi.org/10.1016/j.media.2019.101602.

Li H, Habes M, Wolk DA, Fan Y: A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data. Alzheimers Dement 15(8): 1059-1070, Aug 2019 Notes: https://doi.org/10.1016/j.jalz.2019.02.007.

Jing R, Li P, Ding Z, Lin X, Zhao R, Shi L, Yan H, Liao J, Zhuo C, Lu L, Fan Y: Machine learning identifies unaffected first-degree relatives with functional network patterns and cognitive impairment similar to those of schizophrenia patients. Hum Brain Mapp 40(13): 3930-3939, Sep 2019 Notes: https://doi.org/10.1002/hbm.24678.

Wetherill RR, Rao H, Hager N, Wang J, Franklin TR, Fan Y: Classifying and characterizing nicotine use disorder with high accuracy using machine learning and resting-state fMRI. Addict Biol 24(4): 811-821, Jun 2019 Notes: https://doi.org/10.1111/adb.12644.

Li H, Galperin-Aizenberg M, Pryma D, Simone CB 2nd, Fan Y: Unsupervised machine learning of radiomic features for predicting treatment response and overall survival of early stage non-small cell lung cancer patients treated with stereotactic body radiation therapy. Radiother Oncol 129(2): 218-226, Nov 2018 Notes: https://doi.org/10.1016/j.radonc.2018.06.025.

Zhu X, Zhang W, Fan Y: A Robust Reduced Rank Graph Regression Method for Neuroimaging Genetic Analysis. Neuroinformatics 16(3-4): 351-361, Oct 2018 Notes: https://doi.org/10.1007/s12021-018-9382-0.

Zhao X, Wu Y, Song G, Li Z, Zhang Y, Fan Y: A deep learning model integrating FCNNs and CRFs for brain tumor segmentation. Med Image Anal 43: 98-111, Jan 2018 Notes: https://doi.org/10.1016/j.media.2017.10.002.

Han Y, Cheng H, Toledo JB, Wang X, Li B, Han Y, Wang K, Fan Y: Impaired functional default mode network in patients with mild neurological Wilson's disease. Parkinsonism Relat Disord 30: 46-51, Sep 2016 Notes: https://doi.org/10.1016/j.parkreldis.2016.06.018.

Zhu H, Cheng H, Yang X, Fan Y: Metric Learning for Multi-atlas based Segmentation of Hippocampus. Neuroinformatics 15(1): 41–50, Jan 2017 Notes: https://doi.org/10.1007/s12021-016-9312-y.

Li H, Satterthwaite TD, Fan Y: Large-scale sparse functional networks from resting state fMRI. Neuroimage 156: 1-13, Aug 2017 Notes: https://doi.org/10.1016/j.neuroimage.2017.05.004.

Zheng Q, Furth SL, Tasian GE, Fan Y: Computer-aided diagnosis of congenital abnormalities of the kidney and urinary tract in children based on ultrasound imaging data by integrating texture image features and deep transfer learning image features. J Pediatr Urol 15(1): 75.e1-75.e7, Feb 2019 Notes: https://doi.org/10.1016/j.jpurol.2018.10.020.

Jing R, Han Y, Cheng H, Han Y, Wang K, Weintraub D, Fan Y: Altered large-scale functional brain networks in neurological Wilson's disease. Brain Imaging Behav 14(5): 1445-1455, Oct 2020 Notes: https://doi.org/10.1007/s11682-019-00066-y.

Li P, Jing RX, Zhao RJ, Shi L, Sun HQ, Ding Z, Lin X, Lu L, Fan Y: Association between functional and structural connectivity of the corticostriatal network in people with schizophrenia and unaffected first-degree relatives. J Psychiatry Neurosci 45(6): 395-405, Nov 2020 Notes: https://doi.org/10.1503/jpn.190015.

Cheng H, Gao L, Hou B, Feng F, Guo X, Wang Z, Feng M, Xing B, Fan Y: Reversibility of cerebral blood flow in patients with Cushing's disease after surgery treatment. Metabolism 104(154050): 1-7, Mar 2020 Notes: https://doi.org/10.1016/j.metabol.2019.154050.

Cui Z, Li H, Xia CH, Larsen B, Adebimpe A, Baum GL, Cieslak M, Gur RE, Gur RC, Moore TM, Oathes DJ, Alexander-Bloch AF, Raznahan A, Roalf DR, Shinohara RT, Wolf DH, Davatzikos C, Bassett DS, Fair DA, Fan Y, Satterthwaite TD: Individual Variation in Functional Topography of Association Networks in Youth. Neuron 106(2): 340-353.e8, Apr 2020 Notes: https://doi.org/10.1016/j.neuron.2020.01.029.

Jiao Z, Li H, Xiao Y, Dorsey J, Simone CB, Feigenberg S, Kao G, Fan Y: Integration of deep learning radiomics and counts of circulating tumor cells improves prediction of outcomes of early stage NSCLC patients treated with SBRT. Int J Radiat Oncol Biol Phys 112(4): 1045-1054, Mar 2022 Notes: https://doi.org/10.1016/j.ijrobp.2021.11.006.

Pines AR, Larsen B, Cui Z, Sydnor VJ, Bertolero MA, Adebimpe A, Alexander-Bloch AF, Davatzikos C, Fair DA, Gur RC, Gur RE, Li H, Milham MP, Moore TM, Murtha K, Parkes L, Thompson-Schill SL, Shanmugan S, Shinohara RT, Weinstein SM, Bassett DS, Fan Y, Satterthwaite TD: Dissociable multi-scale patterns of development in personalized brain networks. Nat Commun 13(1): 2647: 1-15, May 2022 Notes: https://doi.org/10.1038/s41467-022-30244-4.

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Last updated: 06/13/2024
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